
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

### so that u dont have warnings
from warnings import filterwarnings
filterwarnings('ignore')


#read dataset
df=pd.read_csv('zomato.csv')
df.head()


df.shape

(51717, 17)


df.dtypes

url                            object
address                        object
name                           object
online_order                   object
book_table                     object
rate                           object
votes                           int64
phone                          object
location                       object
rest_type                      object
dish_liked                     object
cuisines                       object
approx_cost(for two people)    object
reviews_list                   object
menu_item                      object
listed_in(type)                object
listed_in(city)                object
dtype: object


len(df['name'].unique())

8792


df.isna().sum()

url                                0
address                            0
name                               0
online_order                       0
book_table                         0
rate                            7775
votes                              0
phone                           1208
location                          21
rest_type                        227
dish_liked                     28078
cuisines                          45
approx_cost(for two people)      346
reviews_list                       0
menu_item                          0
listed_in(type)                    0
listed_in(city)                    0
dtype: int64


feature_na=[feature for feature in df.columns if df[feature].isnull().sum()>0]
feature_na

['rate',
 'phone',
 'location',
 'rest_type',
 'dish_liked',
 'cuisines',
 'approx_cost(for two people)']


#% of missing values
for feature in feature_na:
    print(f'{feature} has {np.round(((df[feature].isnull().sum()/len(df))*100),3)} % missing values')

rate has 15.034 % missing values
phone has 2.336 % missing values
location has 0.041 % missing values
rest_type has 0.439 % missing values
dish_liked has 54.292 % missing values
cuisines has 0.087 % missing values
approx_cost(for two people) has 0.669 % missing values


df['rate'].unique()

array(['4.1/5', '3.8/5', '3.7/5', '3.6/5', '4.6/5', '4.0/5', '4.2/5',
       '3.9/5', '3.1/5', '3.0/5', '3.2/5', '3.3/5', '2.8/5', '4.4/5',
       '4.3/5', 'NEW', '2.9/5', '3.5/5', nan, '2.6/5', '3.8 /5', '3.4/5',
       '4.5/5', '2.5/5', '2.7/5', '4.7/5', '2.4/5', '2.2/5', '2.3/5',
       '3.4 /5', '-', '3.6 /5', '4.8/5', '3.9 /5', '4.2 /5', '4.0 /5',
       '4.1 /5', '3.7 /5', '3.1 /5', '2.9 /5', '3.3 /5', '2.8 /5',
       '3.5 /5', '2.7 /5', '2.5 /5', '3.2 /5', '2.6 /5', '4.5 /5',
       '4.3 /5', '4.4 /5', '4.9/5', '2.1/5', '2.0/5', '1.8/5', '4.6 /5',
       '4.9 /5', '3.0 /5', '4.8 /5', '2.3 /5', '4.7 /5', '2.4 /5',
       '2.1 /5', '2.2 /5', '2.0 /5', '1.8 /5'], dtype=object)


df.dropna(axis='index',subset=['rate'],inplace=True)


df.shape

(43942, 17)


def split(x):
    return x.split('/')[0]


df['rate']=df['rate'].apply(split)


df.head()


df['rate'].unique()

array(['4.1', '3.8', '3.7', '3.6', '4.6', '4.0', '4.2', '3.9', '3.1',
       '3.0', '3.2', '3.3', '2.8', '4.4', '4.3', 'NEW', '2.9', '3.5',
       '2.6', '3.8 ', '3.4', '4.5', '2.5', '2.7', '4.7', '2.4', '2.2',
       '2.3', '3.4 ', '-', '3.6 ', '4.8', '3.9 ', '4.2 ', '4.0 ', '4.1 ',
       '3.7 ', '3.1 ', '2.9 ', '3.3 ', '2.8 ', '3.5 ', '2.7 ', '2.5 ',
       '3.2 ', '2.6 ', '4.5 ', '4.3 ', '4.4 ', '4.9', '2.1', '2.0', '1.8',
       '4.6 ', '4.9 ', '3.0 ', '4.8 ', '2.3 ', '4.7 ', '2.4 ', '2.1 ',
       '2.2 ', '2.0 ', '1.8 '], dtype=object)


df.replace('NEW',0,inplace=True)


df.replace('-',0,inplace=True)


df['rate']=df['rate'].astype(float)


df.groupby('name')['rate'].mean().nlargest(20).plot.bar()

<AxesSubplot:xlabel='name'>


df_rate=df.groupby('name')['rate'].mean().to_frame()
df_rate=df_rate.reset_index()
df_rate.columns=['restaurant','rating']
df_rate.rating = round(df_rate.rating,2)
df_rate.head(20)


df_rate.shape

(7162, 2)


sns.set_style(style='darkgrid')
sns.distplot(df_rate['rating'])

<AxesSubplot:xlabel='rating', ylabel='Density'>


plt.figure(figsize=(10,7))
chains=df['name'].value_counts()[0:20]
sns.barplot(x=chains,y=chains.index,palette='deep')
plt.title("Most famous restaurants chains in Bangaluru",fontsize = 17)
plt.xlabel("Number of outlets")

Text(0.5, 0, 'Number of outlets')


x=df['online_order'].value_counts()
labels=['accepted','not accepted']
plt.pie(x,explode=[0.0,0.1],autopct='%1.1f%%',labels=labels)

([<matplotlib.patches.Wedge at 0x28dd6b09dc0>,
  <matplotlib.patches.Wedge at 0x28dd6b154f0>],
 [Text(-0.481488774517003, 0.9890240442042423, 'accepted'),
  Text(0.5252605823084886, -1.0789352717716423, 'not accepted')],
 [Text(-0.26263024064563795, 0.5394676604750411, '64.4%'),
  Text(0.30640200634661835, -0.629378908533458, '35.6%')])


!pip install plotly

Requirement already satisfied: plotly in d:\anaconda\lib\site-packages (5.1.0)
Requirement already satisfied: tenacity>=6.2.0 in d:\anaconda\lib\site-packages (from plotly) (8.0.0)
Requirement already satisfied: six in d:\anaconda\lib\site-packages (from plotly) (1.15.0)


import plotly.express as px


x=df['online_order'].value_counts()
labels=['accepted','not accepted']


fig = px.pie(values=x, names=labels,title='Pie chart')
fig.show()


import plotly.graph_objs as go
from plotly.offline import iplot


x=df['book_table'].value_counts()
labels=['not book','book']


trace=go.Pie(labels=labels, values=x,
               hoverinfo='label+percent', textinfo='value', 
               textfont=dict(size=25),
              pull=[ 0.2, 0]
               )

iplot([trace])


df['rest_type'].isna().sum()

151


df['rest_type'].dropna(axis = 'index',inplace=True)


len(df['rest_type'].unique())

88


trace1 = go.Bar( 
        x = df['rest_type'].value_counts().nlargest(20).index,
        y = df['rest_type'].value_counts().nlargest(20),
        name= 'rest_type')


iplot([trace1])


trace1 = go.Bar( 
        x = df.groupby('name')['votes'].max().nlargest(10).index,
        y = df.groupby('name')['votes'].max().nlargest(10),
        name= ' highest voted')

iplot([trace1])


df.groupby('location')['name'].unique()

location
BTM                  [Sankranthi Veg Restaurant, Hearts Unlock Cafe...
Banashankari         [Jalsa, Spice Elephant, San Churro Cafe, Addhu...
Banaswadi            [Cafe Nibras, The Sanctuary, Crunch Pizzas, Pi...
Bannerghatta Road    [Deja Vu Resto Bar, Fattoush, Empire Restauran...
Basavanagudi         [Grand Village, Timepass Dinner, Srinathji's C...
                                           ...                        
West Bangalore       [FreshMenu, Fit Dish Fetish, Garden City Mobil...
Whitefield           [Imperio Cafe, Night Diaries, LocalHost, AB's ...
Wilson Garden        [Tree Top, Sahana's (Nati Style), Karavali Kol...
Yelahanka            [Prashanth Naati Corner, Cheta's Kitchen, Twis...
Yeshwantpur          [Chef's Bank, New Agarwal Bhavan, Fishing Boat...
Name: name, Length: 92, dtype: object


restaurant=[]
location=[]
for key,location_df in df.groupby('location'):
    location.append(key)
    restaurant.append(len(location_df['name'].unique()))


df_total=pd.DataFrame(zip(location,restaurant))
df_total.columns=['location','restaurant']
df_total.set_index('location',inplace=True)
df_total.sort_values('restaurant').tail(10)


df_total.sort_values(by='restaurant').tail(10).plot.bar()

<AxesSubplot:xlabel='location'>


df_total.sort_values(by='restaurant').tail(10).index

Index(['Bellandur', 'Jayanagar', 'Bannerghatta Road', 'JP Nagar',
       'Indiranagar', 'Electronic City', 'Marathahalli', 'HSR', 'BTM',
       'Whitefield'],
      dtype='object', name='location')


trace1 = go.Bar( 
        x = df_total['restaurant'].nlargest(10).index,
        y = df_total['restaurant'].nlargest(10),
        name= 'Priority')


iplot([trace1])


df.isnull().sum()

url                                0
address                            0
name                               0
online_order                       0
book_table                         0
rate                               0
votes                              0
phone                            832
location                           0
rest_type                        151
dish_liked                     20333
cuisines                          11
approx_cost(for two people)      252
reviews_list                       0
menu_item                          0
listed_in(type)                    0
listed_in(city)                    0
dtype: int64


df['cuisines']

0                     North Indian, Mughlai, Chinese
1                        Chinese, North Indian, Thai
2                             Cafe, Mexican, Italian
3                         South Indian, North Indian
4                           North Indian, Rajasthani
                            ...                     
51709                      North Indian, Continental
51711    Andhra, South Indian, Chinese, North Indian
51712                                    Continental
51715                                    Finger Food
51716         Finger Food, North Indian, Continental
Name: cuisines, Length: 43942, dtype: object


cuisines=df['cuisines'].value_counts()[:10]
sns.barplot(cuisines,cuisines.index)
plt.xlabel('Count')
plt.title("Most popular cuisines of Bangalore")

Text(0.5, 1.0, 'Most popular cuisines of Bangalore')


cuisines=df['cuisines'].value_counts()[:10]
trace1 = go.Bar( 
        x = cuisines.index,
        y = cuisines,
        name= 'Cuisines')


iplot([trace1])


len(df['approx_cost(for two people)'].value_counts())

66


df['approx_cost(for two people)'].isna().sum()

252


df.dropna(axis='index',subset=['approx_cost(for two people)'],inplace=True)


df['approx_cost(for two people)'].isna().sum()

0


df['approx_cost(for two people)'].unique()

array(['800', '300', '600', '700', '550', '500', '450', '650', '400',
       '900', '200', '750', '150', '850', '100', '1,200', '350', '250',
       '950', '1,000', '1,500', '1,300', '199', '80', '1,100', '160',
       '1,600', '230', '130', '1,700', '1,400', '1,350', '2,200', '2,000',
       '1,800', '1,900', '180', '330', '2,500', '2,100', '3,000', '2,800',
       '3,400', '50', '40', '1,250', '3,500', '4,000', '2,400', '2,600',
       '1,450', '70', '3,200', '560', '240', '360', '6,000', '1,050',
       '2,300', '4,100', '120', '5,000', '3,700', '1,650', '2,700',
       '4,500'], dtype=object)


df['approx_cost(for two people)'].dtype

dtype('O')


type(df['approx_cost(for two people)'][0])

str


df['approx_cost(for two people)'] = df['approx_cost(for two people)'].apply(lambda x: x.replace(',',''))


df['approx_cost(for two people)']=df['approx_cost(for two people)'].astype(int)


plt.figure(figsize=(14,7))
sns.scatterplot(x="rate",y='approx_cost(for two people)',hue='online_order',data=df)
plt.show()


df.head()


fig = px.box(df,x='online_order',y='approx_cost(for two people)')
fig.show()


df['approx_cost(for two people)'].min()

40


df['approx_cost(for two people)'].max()

6000


df[df['approx_cost(for two people)']==6000]


df[df['approx_cost(for two people)']==6000]['name']

19139    Le Cirque Signature - The Leela Palace
45618    Le Cirque Signature - The Leela Palace
Name: name, dtype: object


sns.set_style('dark')
plt.figure(figsize=(14,7))
sns.distplot(df['approx_cost(for two people)'])
plt.show()


df[df['approx_cost(for two people)']==6000][['name','cuisines','dish_liked']]


data=df.copy()


data.dtypes

url                             object
address                         object
name                            object
online_order                    object
book_table                      object
rate                           float64
votes                            int64
phone                           object
location                        object
rest_type                       object
dish_liked                      object
cuisines                        object
approx_cost(for two people)      int32
reviews_list                    object
menu_item                       object
listed_in(type)                 object
listed_in(city)                 object
dtype: object


data.set_index('name',inplace=True)


data['approx_cost(for two people)'].nlargest(10).plot.bar()

<AxesSubplot:xlabel='name'>


trace1 = go.Bar( 
        x = data['approx_cost(for two people)'].nsmallest(10).index,
        y = data['approx_cost(for two people)'].nsmallest(10),
        name= 'Priority')
iplot([trace1])


data[data['approx_cost(for two people)']<=500]


df_new=df[df['approx_cost(for two people)']<=500]
len(df_new['name'].unique())

4936


location=[]
total=[]
for loc,location_df in df_new.groupby('location'):
    location.append(loc)
    total.append(len(location_df['name'].unique()))


len(location)

90


len(total)

90


location_df=pd.DataFrame(zip(location,total))
location_df.columns=['location','restaurant']
location_df.set_index('location',inplace=True)


location_df.head(20)


type(location)

list


location_df['restaurant'].nlargest(10).plot.bar()
plt.gcf().autofmt_xdate()
plt.ylabel('Total restaurants')

Text(0, 0.5, 'Total restaurants')


trace1 = go.Bar( 
        x = location_df['restaurant'].nlargest(10).index,
        y = location_df['restaurant'].nlargest(10),
        name= 'Priority')
iplot([trace1])


location=[]
total=[]
for loc,location_df in df_new.groupby('location'):
    location.append(loc)
    total.append(location_df['name'].unique())


afford=pd.DataFrame(zip(location,total))
afford.columns=['location','res_names']
afford.set_index('location',inplace=True)
afford.head()


def return_budget(location,restaurant):
    budget=df[(df['approx_cost(for two people)']<=400) & (df['location']==location) 
              & (df['rest_type']==restaurant)]
    return(budget['name'].unique())


return_budget('BTM',"Cafe")

array(['Kullad Cafe', 'Insta Cafe', 'Black Cup Cafe', 'Cafe 221B',
       'Coco Barista', 'Cafe Orio', 'Cafe Longing'], dtype=object)


plt.figure(figsize=(10,7))
Restaurant_locations=df['location'].value_counts()[:20]
sns.barplot(Restaurant_locations,Restaurant_locations.index)

<AxesSubplot:xlabel='location'>


Restaurant_locations=df['location'].value_counts()[:20]
trace1 = go.Bar( 
        x = Restaurant_locations.index,
        y = Restaurant_locations,
        name= 'Priority')
iplot([trace1])


df.shape

(43690, 17)


len(df['location'].unique())

92


locations=pd.DataFrame({"Name":df['location'].unique()})


locations['new_Name']='Bangalore '+locations['Name']


locations.head()


!pip install geopy

Requirement already satisfied: geopy in d:\anaconda\lib\site-packages (2.2.0)
Requirement already satisfied: geographiclib<2,>=1.49 in d:\anaconda\lib\site-packages (from geopy) (1.52)


from geopy.geocoders import Nominatim


lat_lon=[]
geolocator=Nominatim(user_agent="app")
for location in locations['Name']:
    location = geolocator.geocode(location)
    if location is None:
        lat_lon.append(np.nan)
    else:    
        geo=(location.latitude,location.longitude)
        lat_lon.append(geo)


locations['geo_loc']=lat_lon


locations.head()


locations.to_csv('zomato_locations.csv',index=False)


Rest_locations=pd.DataFrame(df['location'].value_counts().reset_index())


Rest_locations.columns=['Name','count']
Rest_locations.head()


locations.head()


locations.shape

(92, 3)


Rest_locations.shape

(92, 2)


Restaurant_locations=Rest_locations.merge(locations,on='Name',how="left").dropna()


Restaurant_locations.shape

(91, 4)


Restaurant_locations['count'].max()

4237


type(Restaurant_locations['geo_loc'][0])

tuple


def generateBaseMap(default_location=[12.97, 77.59], default_zoom_start=12):
    base_map = folium.Map(location=default_location, zoom_start=default_zoom_start)
    return base_map


Restaurant_locations.isna().sum()

Name        0
count       0
new_Name    0
geo_loc     0
dtype: int64


Restaurant_locations['geo_loc'][0][0]

45.95485055


Restaurant_locations['geo_loc'][0][1]

-112.49659530324134


#### unzip it
lat,lon=zip(*Restaurant_locations['geo_loc'])


type(lat)

tuple


Restaurant_locations['lat']=lat
Restaurant_locations['lon']=lon


Restaurant_locations.head()


!pip install folium

Requirement already satisfied: folium in d:\anaconda\lib\site-packages (0.12.1)
Requirement already satisfied: branca>=0.3.0 in d:\anaconda\lib\site-packages (from folium) (0.4.2)
Requirement already satisfied: jinja2>=2.9 in d:\anaconda\lib\site-packages (from folium) (2.11.3)
Requirement already satisfied: numpy in d:\anaconda\lib\site-packages (from folium) (1.20.1)
Requirement already satisfied: requests in d:\anaconda\lib\site-packages (from folium) (2.25.1)
Requirement already satisfied: MarkupSafe>=0.23 in d:\anaconda\lib\site-packages (from jinja2>=2.9->folium) (1.1.1)
Requirement already satisfied: urllib3<1.27,>=1.21.1 in d:\anaconda\lib\site-packages (from requests->folium) (1.26.4)
Requirement already satisfied: chardet<5,>=3.0.2 in d:\anaconda\lib\site-packages (from requests->folium) (4.0.0)
Requirement already satisfied: certifi>=2017.4.17 in d:\anaconda\lib\site-packages (from requests->folium) (2020.12.5)
Requirement already satisfied: idna<3,>=2.5 in d:\anaconda\lib\site-packages (from requests->folium) (2.10)


import folium
from folium.plugins import HeatMap
basemap=generateBaseMap()


basemap


Restaurant_locations[['lat','lon','count']].values.tolist()

[[45.95485055, -112.49659530324134, 4237.0],
 [12.9343774, 77.628415, 2358.0],
 [18.1475, 41.538889, 2113.0],
 [12.9732913, 77.6404672, 1892.0],
 [12.2655944, 76.6465404, 1849.0],
 [27.64392675, 83.05280519687284, 1711.0],
 [44.3730577, -71.6118577, 1688.0],
 [12.9552572, 77.6984163, 1488.0],
 [12.887979, 77.5970812, 1318.0],
 [12.9400321, 77.6203272, 1103.0],
 [12.9302645, 77.6332585, 1084.0],
 [40.28745, -76.964526, 1084.0],
 [12.93577245, 77.66676103753434, 1078.0],
 [14.5395813, 121.070371, 964.0],
 [-6.2659285, 106.7842561, 963.0],
 [12.9242381, 77.6289059, 913.0],
 [12.9778793, 77.6246697, 901.0],
 [12.93433385, 77.63040639553275, 864.0],
 [29.4534927, -98.6440138, 818.0],
 [15.8876779, 75.7046777, 805.0],
 [13.0221416, 77.6403368, 745.0],
 [13.0027353, 77.5703253, 657.0],
 [12.9417261, 77.5755021, 628.0],
 [50.7721586, 0.09772783661369303, 626.0],
 [38.7385916, -77.5275749, 607.0],
 [33.5935063, -79.0345627, 579.0],
 [12.996845, 77.6130165, 574.0],
 [40.7160591, -74.0070597, 550.0],
 [13.0093455, 77.6377094, 522.0],
 [13.0346384, 77.5681733, 521.0],
 [40.7652844, -76.373824, 493.0],
 [13.0141618, 77.6518539, 491.0],
 [12.9882338, 77.554883, 487.0],
 [31.89376, -88.066644, 475.0],
 [12.9624669, 77.6381958, 426.0],
 [12.9575547, 77.5979099, 390.0],
 [62.442403, -114.3987951, 383.0],
 [51.5230784, -0.7374421, 343.0],
 [51.5154481, -0.0720271, 309.0],
 [12.945245, 77.6269144, 292.0],
 [18.5322493, 73.8499601124847, 277.0],
 [12.9678074, 77.6568367, 262.0],
 [12.988721250000001, 77.58516877601824, 252.0],
 [12.9417812, 77.6160146, 227.0],
 [12.9489339, 77.5968273, 203.0],
 [12.9271867, 77.6266252, 193.0],
 [12.9081487, 77.5553179, 168.0],
 [13.2227, 78.5541977, 165.0],
 [12.9089453, 77.6239038, 157.0],
 [12.973936, 77.6509982, 152.0],
 [12.9931876, 77.5753419, 142.0],
 [12.9932739, 77.5388099, 141.0],
 [34.977289, -78.974578, 140.0],
 [1.306731, 103.8497839, 137.0],
 [13.0258087, 77.6305067, 129.0],
 [1.2847055, 103.84320655721689, 118.0],
 [13.02383, 77.5529215, 112.0],
 [13.0358698, 77.6323597, 111.0],
 [12.9243509, 77.6255562, 92.0],
 [12.9414662, 77.7470942, 91.0],
 [12.9846713, 77.6790908, 91.0],
 [13.0646907, 77.49626895712257, 91.0],
 [12.967576, 77.7150877, 84.0],
 [39.76880625, -86.15345077251979, 77.0],
 [12.773175, 77.7831871, 74.0],
 [6.9233338, 93.9046149, 69.0],
 [17.2510682, 80.1651978, 66.0],
 [13.0227204, 77.595715, 63.0],
 [15.8782951, 74.5084834, 58.0],
 [23.1485712, 81.6048241, 50.0],
 [13.0621474, 77.58006135480495, 47.0],
 [13.2923988, 77.7519261, 31.0],
 [13.0215466, 77.7640586, 30.0],
 [12.957998, 77.6037312, 27.0],
 [38.7801076, -121.5056438, 26.0],
 [12.945048, 77.263004, 24.0],
 [11.9917786, 76.5066292, 23.0],
 [12.9970537, 77.669804, 22.0],
 [12.5607431, 77.4258375, 19.0],
 [12.3872141, 76.6669626, 18.0],
 [13.0217151, 77.7660547, 14.0],
 [13.007516, 77.695935, 11.0],
 [13.0382184, 77.5919, 10.0],
 [12.9055682, 77.5455438, 9.0],
 [12.9176571, 77.4837568, 9.0],
 [13.0101286, 77.5548006, 8.0],
 [13.0011289, 77.6325617, 5.0],
 [13.1006982, 77.5963454, 4.0],
 [12.9274413, 77.5155224, 2.0],
 [12.9546741, 77.5121724, 1.0],
 [13.0329419, 77.5273253, 1.0]]


HeatMap(Restaurant_locations[['lat','lon','count']].values.tolist(),zoom=20,radius=15).add_to(basemap)

<folium.plugins.heat_map.HeatMap at 0x28df72f3f70>


basemap


df.head()


df2= df[df['cuisines']=='North Indian']
df2.head()


north_india=pd.DataFrame(df['location'].value_counts().reset_index())
north_india.columns=['Name','count']
north_india.head()


north_india=north_india.merge(locations,on="Name",how='left').dropna()


north_india.head()


north_india['lan'],north_india['lon']=zip(*north_india['geo_loc'].values)


north_india.drop(['geo_loc'],axis=1)


basemap=generateBaseMap()
HeatMap(north_india[['lan','lon','count']].values.tolist(),zoom=20,radius=15).add_to(basemap)
basemap


df3= df[df['cuisines']=='South Indian']
south_india=df2.groupby(['location'],as_index=False)['url'].agg('count')
south_india.columns=['Name','count']
south_india=south_india.merge(locations,on="Name",how='left').dropna()
south_india['lan'],south_india['lon']=zip(*south_india['geo_loc'].values)


south_india=south_india.drop(['geo_loc'],axis=1)


south_india.head()


basemap=generateBaseMap()
HeatMap(south_india[['lan','lon','count']].values.tolist(),zoom=20,radius=15).add_to(basemap)
basemap


df.head()


df['reviews_list'][0]

'[(\'Rated 4.0\', \'RATED\\n  A beautiful place to dine in.The interiors take you back to the Mughal era. The lightings are just perfect.We went there on the occasion of Christmas and so they had only limited items available. But the taste and service was not compromised at all.The only complaint is that the breads could have been better.Would surely like to come here again.\'), (\'Rated 4.0\', \'RATED\\n  I was here for dinner with my family on a weekday. The restaurant was completely empty. Ambience is good with some good old hindi music. Seating arrangement are good too. We ordered masala papad, panner and baby corn starters, lemon and corrionder soup, butter roti, olive and chilli paratha. Food was fresh and good, service is good too. Good for family hangout.\\nCheers\'), (\'Rated 2.0\', \'RATED\\n  Its a restaurant near to Banashankari BDA. Me along with few of my office friends visited to have buffet but unfortunately they only provide veg buffet. On inquiring they said this place is mostly visited by vegetarians. Anyways we ordered ala carte items which took ages to come. Food was ok ok. Definitely not visiting anymore.\'), (\'Rated 4.0\', \'RATED\\n  We went here on a weekend and one of us had the buffet while two of us took Ala Carte. Firstly the ambience and service of this place is great! The buffet had a lot of items and the good was good. We had a Pumpkin Halwa intm the dessert which was amazing. Must try! The kulchas are great here. Cheers!\'), (\'Rated 5.0\', \'RATED\\n  The best thing about the place is itÃ\x83\\x83Ã\x82\\x83Ã\x83\\x82Ã\x82\\x82Ã\x83\\x83Ã\x82\\x82Ã\x83\\x82Ã\x82\\x92s ambiance. Second best thing was yummy ? food. We try buffet and buffet food was not disappointed us.\\nTest ?. ?? ?? ?? ?? ??\\nQuality ?. ??????????.\\nService: Staff was very professional and friendly.\\n\\nOverall experience was excellent.\\n\\nsubirmajumder85.wixsite.com\'), (\'Rated 5.0\', \'RATED\\n  Great food and pleasant ambience. Expensive but Coll place to chill and relax......\\n\\nService is really very very good and friendly staff...\\n\\nFood : 5/5\\nService : 5/5\\nAmbience :5/5\\nOverall :5/5\'), (\'Rated 4.0\', \'RATED\\n  Good ambience with tasty food.\\nCheese chilli paratha with Bhutta palak methi curry is a good combo.\\nLemon Chicken in the starters is a must try item.\\nEgg fried rice was also quite tasty.\\nIn the mocktails, recommend "Alice in Junoon". Do not miss it.\'), (\'Rated 4.0\', \'RATED\\n  You canÃ\x83\\x83Ã\x82\\x83Ã\x83\\x82Ã\x82\\x82Ã\x83\\x83Ã\x82\\x82Ã\x83\\x82Ã\x82\\x92t go wrong with Jalsa. Never been a fan of their buffet and thus always order alacarteÃ\x83\\x83Ã\x82\\x83Ã\x83\\x82Ã\x82\\x82Ã\x83\\x83Ã\x82\\x82Ã\x83\\x82Ã\x82\\x92. Service at times can be on the slower side but food is worth the wait.\'), (\'Rated 5.0\', \'RATED\\n  Overdelighted by the service and food provided at this place. A royal and ethnic atmosphere builds a strong essence of being in India and also the quality and taste of food is truly authentic. I would totally recommend to visit this place once.\'), (\'Rated 4.0\', \'RATED\\n  The place is nice and comfortable. Food wise all jalea outlets maintain a good standard. The soya chaap was a standout dish. Clearly one of trademark dish as per me and a must try.\\n\\nThe only concern is the parking. It very congested and limited to just 5cars. The basement parking is very steep and makes it cumbersome\'), (\'Rated 4.0\', \'RATED\\n  The place is nice and comfortable. Food wise all jalea outlets maintain a good standard. The soya chaap was a standout dish. Clearly one of trademark dish as per me and a must try.\\n\\nThe only concern is the parking. It very congested and limited to just 5cars. The basement parking is very steep and makes it cumbersome\'), (\'Rated 4.0\', \'RATED\\n  The place is nice and comfortable. Food wise all jalea outlets maintain a good standard. The soya chaap was a standout dish. Clearly one of trademark dish as per me and a must try.\\n\\nThe only concern is the parking. It very congested and limited to just 5cars. The basement parking is very steep and makes it cumbersome\')]'


data=df['reviews_list'][0].lower()
data

'[(\'rated 4.0\', \'rated\\n  a beautiful place to dine in.the interiors take you back to the mughal era. the lightings are just perfect.we went there on the occasion of christmas and so they had only limited items available. but the taste and service was not compromised at all.the only complaint is that the breads could have been better.would surely like to come here again.\'), (\'rated 4.0\', \'rated\\n  i was here for dinner with my family on a weekday. the restaurant was completely empty. ambience is good with some good old hindi music. seating arrangement are good too. we ordered masala papad, panner and baby corn starters, lemon and corrionder soup, butter roti, olive and chilli paratha. food was fresh and good, service is good too. good for family hangout.\\ncheers\'), (\'rated 2.0\', \'rated\\n  its a restaurant near to banashankari bda. me along with few of my office friends visited to have buffet but unfortunately they only provide veg buffet. on inquiring they said this place is mostly visited by vegetarians. anyways we ordered ala carte items which took ages to come. food was ok ok. definitely not visiting anymore.\'), (\'rated 4.0\', \'rated\\n  we went here on a weekend and one of us had the buffet while two of us took ala carte. firstly the ambience and service of this place is great! the buffet had a lot of items and the good was good. we had a pumpkin halwa intm the dessert which was amazing. must try! the kulchas are great here. cheers!\'), (\'rated 5.0\', \'rated\\n  the best thing about the place is itã\x83\\x83ã\x82\\x83ã\x83\\x82ã\x82\\x82ã\x83\\x83ã\x82\\x82ã\x83\\x82ã\x82\\x92s ambiance. second best thing was yummy ? food. we try buffet and buffet food was not disappointed us.\\ntest ?. ?? ?? ?? ?? ??\\nquality ?. ??????????.\\nservice: staff was very professional and friendly.\\n\\noverall experience was excellent.\\n\\nsubirmajumder85.wixsite.com\'), (\'rated 5.0\', \'rated\\n  great food and pleasant ambience. expensive but coll place to chill and relax......\\n\\nservice is really very very good and friendly staff...\\n\\nfood : 5/5\\nservice : 5/5\\nambience :5/5\\noverall :5/5\'), (\'rated 4.0\', \'rated\\n  good ambience with tasty food.\\ncheese chilli paratha with bhutta palak methi curry is a good combo.\\nlemon chicken in the starters is a must try item.\\negg fried rice was also quite tasty.\\nin the mocktails, recommend "alice in junoon". do not miss it.\'), (\'rated 4.0\', \'rated\\n  you canã\x83\\x83ã\x82\\x83ã\x83\\x82ã\x82\\x82ã\x83\\x83ã\x82\\x82ã\x83\\x82ã\x82\\x92t go wrong with jalsa. never been a fan of their buffet and thus always order alacarteã\x83\\x83ã\x82\\x83ã\x83\\x82ã\x82\\x82ã\x83\\x83ã\x82\\x82ã\x83\\x82ã\x82\\x92. service at times can be on the slower side but food is worth the wait.\'), (\'rated 5.0\', \'rated\\n  overdelighted by the service and food provided at this place. a royal and ethnic atmosphere builds a strong essence of being in india and also the quality and taste of food is truly authentic. i would totally recommend to visit this place once.\'), (\'rated 4.0\', \'rated\\n  the place is nice and comfortable. food wise all jalea outlets maintain a good standard. the soya chaap was a standout dish. clearly one of trademark dish as per me and a must try.\\n\\nthe only concern is the parking. it very congested and limited to just 5cars. the basement parking is very steep and makes it cumbersome\'), (\'rated 4.0\', \'rated\\n  the place is nice and comfortable. food wise all jalea outlets maintain a good standard. the soya chaap was a standout dish. clearly one of trademark dish as per me and a must try.\\n\\nthe only concern is the parking. it very congested and limited to just 5cars. the basement parking is very steep and makes it cumbersome\'), (\'rated 4.0\', \'rated\\n  the place is nice and comfortable. food wise all jalea outlets maintain a good standard. the soya chaap was a standout dish. clearly one of trademark dish as per me and a must try.\\n\\nthe only concern is the parking. it very congested and limited to just 5cars. the basement parking is very steep and makes it cumbersome\')]'


import re
data2=re.sub('[^a-zA-Z]',' ',data)
data2

'   rated        rated n  a beautiful place to dine in the interiors take you back to the mughal era  the lightings are just perfect we went there on the occasion of christmas and so they had only limited items available  but the taste and service was not compromised at all the only complaint is that the breads could have been better would surely like to come here again       rated        rated n  i was here for dinner with my family on a weekday  the restaurant was completely empty  ambience is good with some good old hindi music  seating arrangement are good too  we ordered masala papad  panner and baby corn starters  lemon and corrionder soup  butter roti  olive and chilli paratha  food was fresh and good  service is good too  good for family hangout  ncheers      rated        rated n  its a restaurant near to banashankari bda  me along with few of my office friends visited to have buffet but unfortunately they only provide veg buffet  on inquiring they said this place is mostly visited by vegetarians  anyways we ordered ala carte items which took ages to come  food was ok ok  definitely not visiting anymore       rated        rated n  we went here on a weekend and one of us had the buffet while two of us took ala carte  firstly the ambience and service of this place is great  the buffet had a lot of items and the good was good  we had a pumpkin halwa intm the dessert which was amazing  must try  the kulchas are great here  cheers       rated        rated n  the best thing about the place is it   x     x     x     x     x     x     x     x  s ambiance  second best thing was yummy   food  we try buffet and buffet food was not disappointed us  ntest                   nquality                nservice  staff was very professional and friendly  n noverall experience was excellent  n nsubirmajumder   wixsite com      rated        rated n  great food and pleasant ambience  expensive but coll place to chill and relax       n nservice is really very very good and friendly staff    n nfood       nservice       nambience      noverall           rated        rated n  good ambience with tasty food  ncheese chilli paratha with bhutta palak methi curry is a good combo  nlemon chicken in the starters is a must try item  negg fried rice was also quite tasty  nin the mocktails  recommend  alice in junoon   do not miss it       rated        rated n  you can   x     x     x     x     x     x     x     x  t go wrong with jalsa  never been a fan of their buffet and thus always order alacarte   x     x     x     x     x     x     x     x    service at times can be on the slower side but food is worth the wait       rated        rated n  overdelighted by the service and food provided at this place  a royal and ethnic atmosphere builds a strong essence of being in india and also the quality and taste of food is truly authentic  i would totally recommend to visit this place once       rated        rated n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome      rated        rated n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome      rated        rated n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome   '


data3=re.sub('rated', ' ',data2)
data3

'              n  a beautiful place to dine in the interiors take you back to the mughal era  the lightings are just perfect we went there on the occasion of christmas and so they had only limited items available  but the taste and service was not compromised at all the only complaint is that the breads could have been better would surely like to come here again                  n  i was here for dinner with my family on a weekday  the restaurant was completely empty  ambience is good with some good old hindi music  seating arrangement are good too  we ordered masala papad  panner and baby corn starters  lemon and corrionder soup  butter roti  olive and chilli paratha  food was fresh and good  service is good too  good for family hangout  ncheers                 n  its a restaurant near to banashankari bda  me along with few of my office friends visited to have buffet but unfortunately they only provide veg buffet  on inquiring they said this place is mostly visited by vegetarians  anyways we ordered ala carte items which took ages to come  food was ok ok  definitely not visiting anymore                  n  we went here on a weekend and one of us had the buffet while two of us took ala carte  firstly the ambience and service of this place is great  the buffet had a lot of items and the good was good  we had a pumpkin halwa intm the dessert which was amazing  must try  the kulchas are great here  cheers                  n  the best thing about the place is it   x     x     x     x     x     x     x     x  s ambiance  second best thing was yummy   food  we try buffet and buffet food was not disappointed us  ntest                   nquality                nservice  staff was very professional and friendly  n noverall experience was excellent  n nsubirmajumder   wixsite com                 n  great food and pleasant ambience  expensive but coll place to chill and relax       n nservice is really very very good and friendly staff    n nfood       nservice       nambience      noverall                      n  good ambience with tasty food  ncheese chilli paratha with bhutta palak methi curry is a good combo  nlemon chicken in the starters is a must try item  negg fried rice was also quite tasty  nin the mocktails  recommend  alice in junoon   do not miss it                  n  you can   x     x     x     x     x     x     x     x  t go wrong with jalsa  never been a fan of their buffet and thus always order alacarte   x     x     x     x     x     x     x     x    service at times can be on the slower side but food is worth the wait                  n  overdelighted by the service and food provided at this place  a royal and ethnic atmosphere builds a strong essence of being in india and also the quality and taste of food is truly authentic  i would totally recommend to visit this place once                  n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome                 n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome                 n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome   '


data4=re.sub('x',' ',data3)
data4

'              n  a beautiful place to dine in the interiors take you back to the mughal era  the lightings are just perfect we went there on the occasion of christmas and so they had only limited items available  but the taste and service was not compromised at all the only complaint is that the breads could have been better would surely like to come here again                  n  i was here for dinner with my family on a weekday  the restaurant was completely empty  ambience is good with some good old hindi music  seating arrangement are good too  we ordered masala papad  panner and baby corn starters  lemon and corrionder soup  butter roti  olive and chilli paratha  food was fresh and good  service is good too  good for family hangout  ncheers                 n  its a restaurant near to banashankari bda  me along with few of my office friends visited to have buffet but unfortunately they only provide veg buffet  on inquiring they said this place is mostly visited by vegetarians  anyways we ordered ala carte items which took ages to come  food was ok ok  definitely not visiting anymore                  n  we went here on a weekend and one of us had the buffet while two of us took ala carte  firstly the ambience and service of this place is great  the buffet had a lot of items and the good was good  we had a pumpkin halwa intm the dessert which was amazing  must try  the kulchas are great here  cheers                  n  the best thing about the place is it                                                s ambiance  second best thing was yummy   food  we try buffet and buffet food was not disappointed us  ntest                   nquality                nservice  staff was very professional and friendly  n noverall e perience was e cellent  n nsubirmajumder   wi site com                 n  great food and pleasant ambience  e pensive but coll place to chill and rela        n nservice is really very very good and friendly staff    n nfood       nservice       nambience      noverall                      n  good ambience with tasty food  ncheese chilli paratha with bhutta palak methi curry is a good combo  nlemon chicken in the starters is a must try item  negg fried rice was also quite tasty  nin the mocktails  recommend  alice in junoon   do not miss it                  n  you can                                                t go wrong with jalsa  never been a fan of their buffet and thus always order alacarte                                                  service at times can be on the slower side but food is worth the wait                  n  overdelighted by the service and food provided at this place  a royal and ethnic atmosphere builds a strong essence of being in india and also the quality and taste of food is truly authentic  i would totally recommend to visit this place once                  n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome                 n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome                 n  the place is nice and comfortable  food wise all jalea outlets maintain a good standard  the soya chaap was a standout dish  clearly one of trademark dish as per me and a must try  n nthe only concern is the parking  it very congested and limited to just  cars  the basement parking is very steep and makes it cumbersome   '


re.sub(' +',' ',data4)

' n a beautiful place to dine in the interiors take you back to the mughal era the lightings are just perfect we went there on the occasion of christmas and so they had only limited items available but the taste and service was not compromised at all the only complaint is that the breads could have been better would surely like to come here again n i was here for dinner with my family on a weekday the restaurant was completely empty ambience is good with some good old hindi music seating arrangement are good too we ordered masala papad panner and baby corn starters lemon and corrionder soup butter roti olive and chilli paratha food was fresh and good service is good too good for family hangout ncheers n its a restaurant near to banashankari bda me along with few of my office friends visited to have buffet but unfortunately they only provide veg buffet on inquiring they said this place is mostly visited by vegetarians anyways we ordered ala carte items which took ages to come food was ok ok definitely not visiting anymore n we went here on a weekend and one of us had the buffet while two of us took ala carte firstly the ambience and service of this place is great the buffet had a lot of items and the good was good we had a pumpkin halwa intm the dessert which was amazing must try the kulchas are great here cheers n the best thing about the place is it s ambiance second best thing was yummy food we try buffet and buffet food was not disappointed us ntest nquality nservice staff was very professional and friendly n noverall e perience was e cellent n nsubirmajumder wi site com n great food and pleasant ambience e pensive but coll place to chill and rela n nservice is really very very good and friendly staff n nfood nservice nambience noverall n good ambience with tasty food ncheese chilli paratha with bhutta palak methi curry is a good combo nlemon chicken in the starters is a must try item negg fried rice was also quite tasty nin the mocktails recommend alice in junoon do not miss it n you can t go wrong with jalsa never been a fan of their buffet and thus always order alacarte service at times can be on the slower side but food is worth the wait n overdelighted by the service and food provided at this place a royal and ethnic atmosphere builds a strong essence of being in india and also the quality and taste of food is truly authentic i would totally recommend to visit this place once n the place is nice and comfortable food wise all jalea outlets maintain a good standard the soya chaap was a standout dish clearly one of trademark dish as per me and a must try n nthe only concern is the parking it very congested and limited to just cars the basement parking is very steep and makes it cumbersome n the place is nice and comfortable food wise all jalea outlets maintain a good standard the soya chaap was a standout dish clearly one of trademark dish as per me and a must try n nthe only concern is the parking it very congested and limited to just cars the basement parking is very steep and makes it cumbersome n the place is nice and comfortable food wise all jalea outlets maintain a good standard the soya chaap was a standout dish clearly one of trademark dish as per me and a must try n nthe only concern is the parking it very congested and limited to just cars the basement parking is very steep and makes it cumbersome '


dataset=df[df['rest_type']=='Quick Bites']


type(dataset['reviews_list'][3])

str


total_review=' '
for review in dataset['reviews_list']:
    review=review.lower()
    review=re.sub('[^a-zA-Z]', ' ',review)
    review=re.sub('rated', ' ',review)
    review=re.sub('x',' ',review)
    review=re.sub(' +',' ',review)
    total_review=total_review + str(review)


from wordcloud import WordCloud


wordcloud = WordCloud(width = 800, height = 800, 
                background_color ='white', 
                stopwords = stopwords, 
                min_font_size = 10).generate(total_review) 
# plot the WordCloud image                        
plt.figure(figsize = (8, 8)) 
plt.imshow(wordcloud) 
plt.axis("off")


def importance(restaurant):
    dataset=df[df['rest_type']==restaurant]
    total_review=' '
    for review in dataset['reviews_list']:
        review=review.lower()
        review=re.sub('[^a-zA-Z]', ' ',review)
        review=re.sub('rated', ' ',review)
        review=re.sub('x',' ',review)
        review=re.sub(' +',' ',review)
        total_review=total_review + str(review)
    wordcloud = WordCloud(width = 800, height = 800, 
            background_color ='white', 
            stopwords = set(STOPWORDS), 
            min_font_size = 10).generate(total_review) 
    # plot the WordCloud image                        
    plt.figure(figsize = (8, 8)) 
    plt.imshow(wordcloud) 
    plt.axis("off")


importance('Quick Bites')


!jupyter nbconvert --to html Youtube_data_analysis.ipynb

	restaurant	rating
0	#FeelTheROLL	3.40
1	#L-81 Cafe	3.90
2	#refuel	3.70
3	1000 B.C	3.20
4	100ÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂ°C	3.70
5	11 to 11 Express Biriyanis	3.50
6	1131 Bar + Kitchen	4.50
7	12th Main - Grand Mercure	4.10
8	1441 Pizzeria	4.10
9	1522 - The Pub	4.21
10	154 Breakfast Club	4.00
11	1722 Urban Bistro	4.10
12	18+ Ice Cafe	3.50
13	1947	4.02
14	1980s Games Cafe	3.40
15	1992 Chats - Space	3.70
16	1Q1	4.30
17	1TO3 Kitchen	3.10
18	2 Statez	3.70
19	20 Char - Sterlings MAC Hotel	4.00

	Name	new_Name
0	Banashankari	Bangalore Banashankari
1	Basavanagudi	Bangalore Basavanagudi
2	Mysore Road	Bangalore Mysore Road
3	Jayanagar	Bangalore Jayanagar
4	Kumaraswamy Layout	Bangalore Kumaraswamy Layout

	Name	new_Name	geo_loc
0	Banashankari	Bangalore Banashankari	(15.8876779, 75.7046777)
1	Basavanagudi	Bangalore Basavanagudi	(12.9417261, 77.5755021)
2	Mysore Road	Bangalore Mysore Road	(12.3872141, 76.6669626)
3	Jayanagar	Bangalore Jayanagar	(27.64392675, 83.05280519687284)
4	Kumaraswamy Layout	Bangalore Kumaraswamy Layout	(12.9081487, 77.5553179)

	Name	new_Name	geo_loc
0	Banashankari	Bangalore Banashankari	(15.8876779, 75.7046777)
1	Basavanagudi	Bangalore Basavanagudi	(12.9417261, 77.5755021)
2	Mysore Road	Bangalore Mysore Road	(12.3872141, 76.6669626)
3	Jayanagar	Bangalore Jayanagar	(27.64392675, 83.05280519687284)
4	Kumaraswamy Layout	Bangalore Kumaraswamy Layout	(12.9081487, 77.5553179)

	url	address	name	online_order	book_table	rate	votes	phone	location	rest_type	dish_liked	cuisines	approx_cost(for two people)	reviews_list	menu_item	listed_in(type)	listed_in(city)
0	https://www.zomato.com/bangalore/jalsa-banasha...	942, 21st Main Road, 2nd Stage, Banashankari, ...	Jalsa	Yes	Yes	4.1/5	775	080 42297555\r\n+91 9743772233	Banashankari	Casual Dining	Pasta, Lunch Buffet, Masala Papad, Paneer Laja...	North Indian, Mughlai, Chinese	800	[('Rated 4.0', 'RATED\n A beautiful place to ...	[]	Buffet	Banashankari
1	https://www.zomato.com/bangalore/spice-elephan...	2nd Floor, 80 Feet Road, Near Big Bazaar, 6th ...	Spice Elephant	Yes	No	4.1/5	787	080 41714161	Banashankari	Casual Dining	Momos, Lunch Buffet, Chocolate Nirvana, Thai G...	Chinese, North Indian, Thai	800	[('Rated 4.0', 'RATED\n Had been here for din...	[]	Buffet	Banashankari
2	https://www.zomato.com/SanchurroBangalore?cont...	1112, Next to KIMS Medical College, 17th Cross...	San Churro Cafe	Yes	No	3.8/5	918	+91 9663487993	Banashankari	Cafe, Casual Dining	Churros, Cannelloni, Minestrone Soup, Hot Choc...	Cafe, Mexican, Italian	800	[('Rated 3.0', "RATED\n Ambience is not that ...	[]	Buffet	Banashankari
3	https://www.zomato.com/bangalore/addhuri-udupi...	1st Floor, Annakuteera, 3rd Stage, Banashankar...	Addhuri Udupi Bhojana	No	No	3.7/5	88	+91 9620009302	Banashankari	Quick Bites	Masala Dosa	South Indian, North Indian	300	[('Rated 4.0', "RATED\n Great food and proper...	[]	Buffet	Banashankari
4	https://www.zomato.com/bangalore/grand-village...	10, 3rd Floor, Lakshmi Associates, Gandhi Baza...	Grand Village	No	No	3.8/5	166	+91 8026612447\r\n+91 9901210005	Basavanagudi	Casual Dining	Panipuri, Gol Gappe	North Indian, Rajasthani	600	[('Rated 4.0', 'RATED\n Very good restaurant ...	[]	Buffet	Banashankari

	restaurant
location
Bellandur	284
Jayanagar	311
Bannerghatta Road	362
JP Nagar	400
Indiranagar	467
Electronic City	518
Marathahalli	525
HSR	553
BTM	581
Whitefield	634

	url	address	name	online_order	book_table	rate	votes	phone	location	rest_type	dish_liked	cuisines	approx_cost(for two people)	reviews_list	menu_item	listed_in(type)	listed_in(city)
19139	https://www.zomato.com/bangalore/le-cirque-sig...	The Leela Palace, 23, Old Airport Road, Bangalore	Le Cirque Signature - The Leela Palace	No	Yes	4.3	126	080 30571234\r\n080 30571540	Old Airport Road	Fine Dining	Wine, Asparagus Soup, Creme Brulee, Pasta, Rav...	French, Italian	6000	[('Rated 5.0', 'RATED\n Awesome would be an u...	[]	Dine-out	Indiranagar
45618	https://www.zomato.com/bangalore/le-cirque-sig...	The Leela Palace, 23, Old Airport Road, Bangalore	Le Cirque Signature - The Leela Palace	No	Yes	4.3	128	080 30571234\n080 30571540	Old Airport Road	Fine Dining	Wine, Asparagus Soup, Creme Brulee, Pasta, Rav...	French, Italian	6000	[('Rated 5.0', 'RATED\n Awesome would be an u...	[]	Dine-out	Old Airport Road

	restaurant
location
BTM	482
Banashankari	186
Banaswadi	116
Bannerghatta Road	262
Basavanagudi	161
Basaveshwara Nagar	52
Bellandur	197
Bommanahalli	49
Brigade Road	61
Brookefield	113
CV Raman Nagar	26
Central Bangalore	2
Church Street	18
City Market	20
Commercial Street	28
Cunningham Road	21
Domlur	55
East Bangalore	15
Ejipura	42
Electronic City	373

	res_names
location
BTM	[Hearts Unlock Cafe, eat.fit, Hiyar Majhe Kolk...
Banashankari	[Addhuri Udupi Bhojana, CafÃÂÃÂÃÂÃÂÃÂ...
Banaswadi	[Cafe Nibras, The Sanctuary, Pizza Stop, Crunc...
Bannerghatta Road	[Tisano Cafe, Butterly, Black Mug Cafe, #refue...
Basavanagudi	[Chaatimes, Chinese Kitchen, Kabab Magic, Sri ...

	Name	count
0	BTM	4237
1	Koramangala 5th Block	2358
2	HSR	2113
3	Indiranagar	1892
4	JP Nagar	1849

	Name	count	new_Name	geo_loc	lat	lon
0	BTM	4237	Bangalore BTM	(45.95485055, -112.49659530324134)	45.954851	-112.496595
1	Koramangala 5th Block	2358	Bangalore Koramangala 5th Block	(12.9343774, 77.628415)	12.934377	77.628415
2	HSR	2113	Bangalore HSR	(18.1475, 41.538889)	18.147500	41.538889
3	Indiranagar	1892	Bangalore Indiranagar	(12.9732913, 77.6404672)	12.973291	77.640467
4	JP Nagar	1849	Bangalore JP Nagar	(12.2655944, 76.6465404)	12.265594	76.646540

	url	address	name	online_order	book_table	rate	votes	phone	location	rest_type	dish_liked	cuisines	approx_cost(for two people)	reviews_list	menu_item	listed_in(type)	listed_in(city)
5	https://www.zomato.com/bangalore/timepass-dinn...	37, 5-1, 4th Floor, Bosco Court, Gandhi Bazaar...	Timepass Dinner	Yes	No	3.8	286	+91 9980040002\r\n+91 9980063005	Basavanagudi	Casual Dining	Onion Rings, Pasta, Kadhai Paneer, Salads, Sal...	North Indian	600	[('Rated 3.0', 'RATED\n Food 3/5\nAmbience 3/...	[]	Buffet	Banashankari
50	https://www.zomato.com/bangalore/petoo-banasha...	276, Ground Floor, 100 Feet Outer Ring Road, B...	Petoo	No	No	3.7	21	+91 8026893211	Banashankari	Quick Bites	NaN	North Indian	450	[('Rated 2.0', 'RATED\n This is a neatly made...	[]	Delivery	Banashankari
72	https://www.zomato.com/bangalore/spicy-tandoor...	Opposite ICICi Bank, Hanuman Nagar, Banashanka...	Spicy Tandoor	No	No	0.0	0	+91 8050884222	Banashankari	Quick Bites	NaN	North Indian	150	[('Rated 4.0', 'RATED\n cost for chicken roll...	[]	Delivery	Banashankari
87	https://www.zomato.com/bangalore/krishna-sagar...	38, 22nd Main, 22nd Cross, Opposite BDA, 2nd S...	Krishna Sagar	No	No	3.5	31	+91 8892752997\r\n+91 7204780429	Banashankari	Quick Bites	NaN	North Indian	200	[('Rated 1.0', 'RATED\n Worst experience with...	[]	Delivery	Banashankari
94	https://www.zomato.com/bangalore/nandhini-delu...	304, Opposite Apollo Public School, 100 Feet R...	Nandhini Deluxe	No	No	2.6	283	080 26890011\r\n080 26890033	Banashankari	Casual Dining	Biryani, Chicken Guntur, Thali, Buttermilk, Ma...	North Indian	600	[('Rated 3.0', 'RATED\n Ididnt like much.\n\n...	[]	Delivery	Banashankari

Columns description¶

getting all NAN features¶

calculate avg rating of each resturant¶

Rating distribution¶

Almost more than 50 percent of restaurants has rating between 3 and 4. Restaurants having rating more than 4.5 are very rare.¶

Which are the top restaurant chains in Bangaluru?¶

How many of the restuarants do not accept online orders?¶

using plotly, How many of the restuarants do not accept online orders?¶

What is the ratio b/w restaurants that provide and do not provide table booking ?¶

How many types of restaurants we have?¶

now using plotly¶

At all, Banglore is known as the tech capital of India,people having busy and modern life will prefer Quick Bites.¶

highest voted restaurant¶

total restaurants at different locations of Bengalore¶

Total number of variety of restaurants ie north indian,south Indian¶

We can observe that North Indian,chinese,South Indian and Biriyani are most common.¶

It means Bengalore is more influenced by North Indian culture more than South¶

Analyse Approx cost for 2 people¶

cost vs rating¶

Is there any difference b/w price of restaurants accepting and not accepting online orders?¶

Cheapest Rate for 2 people¶

Most costly for 2 people¶

distribution of cost for 2 people¶

most of the price lies between in a range of under 1000,it means most are affordable & very few are luxurious¶

Most costly Rate for 2 people is served at which Restaurant what exactly is the dish involved in this and liked dish of that restaurant¶

Top 10 Most Expensive restaurant with approx cost for 2 people¶

Top 10 Cheapest restaurant with approx cost for 2 people¶

all the restautant that are below than 500(budget hotel)¶

Total no. of Restaurants that have better rating >4 and that are under budget too ie less than 500¶

Total such various affordable hotels at different location¶

To Visualise what are the names of those hotels¶

Finding Best budget Restaurants in any location¶

we will pass location and restaurant type as parameteres,function will return name of restaurants.¶

Which are the foodie areas?¶

We can see that BTM,HSR and Koranmangala 5th block has the most number of restaurants.¶

BTM dominates the section by having more than 4000 restaurants.¶

geographical analysis¶

I need Latitudes & longitudes for each of the place for geaographical Data analysis,so to fetch lat,lon of each place,use Geopy¶

We have found out latitude and longitude of each location listed in the dataset using geopy.¶

This is used to plot maps.¶

now combine both the dataframes¶

It is clear that restaurants tend to concentrate in central bangalore area. The cluster of restaurants lowers are we move away from central.

note heatmap is good when we have latitude,longitude or imporatnce of that particular place or count of that place¶

Heatmap of North Indian restaurants¶

What about South Indian cuisines?¶

analysing Reviews of Particular Restaurant¶

remove multiple spaces¶

analyse review of a particular restaurant¶

It is clear that restaurants tend to concentrate in central bangalore area.

The cluster of restaurants lowers are we move away from central.